Applied Machine Learning: An Efficient Clustering Based Classification Model for OnlineProduct Reviews Using Support Vector Machines and K-means A - Softcover
Synopsis
This study presents a hybrid model that leverages the strengths of K-means clustering and Support Vector Machines (SVM) for classifying online product reviews. K-means is used to group reviews into clusters, reducing data complexity and improving feature extraction. Subsequently, SVM is employed to classify the clustered data into positive, negative, or neutral sentiments. The combined approach enhances classification accuracy, reduces computational cost, and effectively handles large datasets. Experimental results demonstrate that the proposed model outperforms traditional standalone classifiers in terms of precision, recall, and overall accuracy.
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Applied Machine Learning (Paperback)
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Paperback. Condition: new. Paperback. This study presents a hybrid model that leverages the strengths of K-means clustering and Support Vector Machines (SVM) for classifying online product reviews. K-means is used to group reviews into clusters, reducing data complexity and improving feature extraction. Subsequently, SVM is employed to classify the clustered data into positive, negative, or neutral sentiments. The combined approach enhances classification accuracy, reduces computational cost, and effectively handles large datasets. Experimental results demonstrate that the proposed model outperforms traditional standalone classifiers in terms of precision, recall, and overall accuracy. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Seller Inventory # 9786208432119
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Applied Machine Learning
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Applied Machine Learning
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Applied Machine Learning: An Efficient Clustering Based Classification Model for OnlineProduct Reviews Using Support Vector Machines and K-means A
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Applied Machine Learning (Paperback)
Published by
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ISBN 10: 6208432111
ISBN 13: 9786208432119
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Paperback. Condition: new. Paperback. This study presents a hybrid model that leverages the strengths of K-means clustering and Support Vector Machines (SVM) for classifying online product reviews. K-means is used to group reviews into clusters, reducing data complexity and improving feature extraction. Subsequently, SVM is employed to classify the clustered data into positive, negative, or neutral sentiments. The combined approach enhances classification accuracy, reduces computational cost, and effectively handles large datasets. Experimental results demonstrate that the proposed model outperforms traditional standalone classifiers in terms of precision, recall, and overall accuracy. This item is printed on demand. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability. Seller Inventory # 9786208432119
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Applied Machine Learning (Paperback)
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ISBN 10: 6208432111
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Paperback. Condition: new. Paperback. This study presents a hybrid model that leverages the strengths of K-means clustering and Support Vector Machines (SVM) for classifying online product reviews. K-means is used to group reviews into clusters, reducing data complexity and improving feature extraction. Subsequently, SVM is employed to classify the clustered data into positive, negative, or neutral sentiments. The combined approach enhances classification accuracy, reduces computational cost, and effectively handles large datasets. Experimental results demonstrate that the proposed model outperforms traditional standalone classifiers in terms of precision, recall, and overall accuracy. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Seller Inventory # 9786208432119
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Applied Machine Learning | An Efficient Clustering Based Classification Model for OnlineProduct Reviews Using Support Vector Machines and K-means A
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Taschenbuch. Condition: Neu. Applied Machine Learning | An Efficient Clustering Based Classification Model for OnlineProduct Reviews Using Support Vector Machines and K-means A | Vijayaragavan P | Taschenbuch | Englisch | 2025 | LAP LAMBERT Academic Publishing | EAN 9786208432119 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu. Seller Inventory # 131816901
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Applied Machine Learning
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Taschenbuch. Condition: Neu. Neuware -This study presents a hybrid model that leverages the strengths of K-means clustering and Support Vector Machines (SVM) for classifying online product reviews. K-means is used to group reviews into clusters, reducing data complexity and improving feature extraction. Subsequently, SVM is employed to classify the clustered data into positive, negative, or neutral sentiments. The combined approach enhances classification accuracy, reduces computational cost, and effectively handles large datasets. Experimental results demonstrate that the proposed model outperforms traditional standalone classifiers in terms of precision, recall, and overall accuracy.Books on Demand GmbH, Überseering 33, 22297 Hamburg 172 pp. Englisch. Seller Inventory # 9786208432119
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Applied Machine Learning : An Efficient Clustering Based Classification Model for OnlineProduct Reviews Using Support Vector Machines and K-means A
Published by
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ISBN 10: 6208432111
ISBN 13: 9786208432119
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